I cannot get the calculation to work for the life of me in a way that makes sense. It seems you gave a few variations in how to calculate the average customer rate of return and when I put it into my numbers, they all vary in the output.

1st Formula: (ARR – ACS)/CAC
2nd Formula: (ARR – ACS)/ ARR x (ARR/CAC) where (ARR-ACS)/ARR = Contribition Margin and (ARR/CAC)= The Saas Magic Number
3rd Formula: (ARR-ACS)/# of Customers)/(CAC/# of New Customers)

Am I missing something?

It is difficult to give a good answer without seeing the actual calculations, but my first impressions are the following.

1) I would not adjust for network effects, these rightfully increase J (customer rate of return), because you are spending less to acquire customers when you have strong word of mouth. This is good, and it should show up as a higher J. I usually handle wide variations simply by using a moving average for CAC and ACS. ARR is generally very stable.

2) 5 seems very high…so to confirm the calculation formula for J
a) are you including all sales/marketing staff costs in CAC?
b) are you including all product/service/admin costs in ACS?
c) are you using new customers to calculate CAC,
but total customers to calculate ARR and ACS?
d) are ARR and ACS measured in annual recurring costs?
(this should be the case even if your measurement period is semester)

3) It seems unusual that CAC should vary so dramatically…what is the source of variation?
a) are out of pocket acquisition costs larger than staffing costs?
b) are the number of new customers small, e.g., 1 then 5, then 2, etc.

4) I would first recommend coming up with formulas (probably 6 month moving averages) that accurately represent stable values for average CAC, ARR and ACS separately. Then you can be sure your J is correct…even if it is 5!

…if you want to email me a spreadsheet to jyork [at] chaotic-flow.com, I’d be happy to take a look and email you back better answers confidentially.

Regards,

Joel

first thanks for your good work on chaotic-flow!

While computing CAC RATIO/j related metrics for my own B2B SaaS company I two points that appear to be interesting:

First:

Sometimes, during periods of low investment in CAC, we still had grow.. I understand that most of this growth should be attributed to mouth-to-mouth/network effects not our direct sales/mktg efforts or past CACs (something that I’ll comment later below).

As we had growth but with a low CAC, our J number was very high (5, for example) during this period, giving misleading information at a first glance (a very appealing ROI)

Is there, on your vision, a good way to adjust to this fact?

I thought on an adjusted version that discounts the network effects:

original J = (ARR(t) – ACS(t))/CAC(t-1)

adjusted J = (ARR(t) – ACS(t) – a(ARR(t-1)-ACS(t-1) ) )/CAC(t-1)

where a is the supposed growth due to network effects (10%, for example)

Second:

We work with semesterly metrics as they are fit better our sales cycles. Most of the leads are converted or not during this 6-months period. But sometimes (I would say 30% of the cases), we see old prospects returning and closing the deal without more efforts! Something that is not attributed to CAC(t-1), but to CAC(t-2) or even CAC(t-3)

What do you think on this two cases?

Alex